Generally, one commonly-used technique for compressing digital images is a JPEG technique, named for the Joint Photographic Experts Group (JPEG), the committee that developed the specifications for standard use of the technique and for the standard storage format of JPEG image files. The JPEG technique is “lossy”. That is, an image that has been compressed by the JPEG technique and then reconstituted is not identical to the original, uncompressed image.
In related art image compression methods, a Differential pulse-code modulation (DPCM) or a Pulse-code modulation (PCM) is used to encode an entire image approximately within a pre-defined number of bits in a constant bitrate scenario or to encode an entire image approximately at pre-defined quality in a constant quality scenario. In this method, top, left, and top left pixels are subtracted from a current pixel to get a residual value which is quantized, and the quantization factor determines the mode of encoding. The code length computation is performed for all the quantized values. The quantization is not adaptive i.e., the quantization is uniform for each block of the image.
In other related art image compression methods, the image samples are transformed and quantized by using Discrete Cosine Transform (DCT), run-length encoding (RLE), and Huffman encoding. Here, the method uses a separate control structure for random accessibility. The encoded size of the blocks can be different and no fixed bit budget per block is maintained.
Related art image compression methods are unable to exploit visual masking and other properties of the Human Visual System (HVS) which vary spatially with image content. This is because the quantization parameters used by these algorithms are typically constant over the extent of the image. As a result, images are unable to be compressed efficiently. Also, to achieve a target bit-rate or visual quality using these systems, the image must be compressed multiple times.